Machine Learning Evaluation Metrics in R
Last Updated on August 22, 2019
What metrics can you use to evaluate your machine learning algorithms?
In this post you will discover how you can evaluate your machine learning algorithms in R using a number of standard evaluation metrics.
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Machine Learning Evaluation Metrics in R
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Model Evaluation Metrics in R
There are many different metrics that you can use to evaluate your machine learning algorithms in R.
When you use caret to evaluate your models, the default metrics used are accuracy for classification problems and RMSE for regression. But caret supports a range of other popular evaluation metrics.
In the next section you will step through each of the evaluation metrics provided by caret. Each example provides a complete case study that you can copy-and-paste into your project and adapt to your problem.